def __init__(self, parent, sharedGLWidget, logger=PrintLogger()):
super().__init__(parent)
self.logger = logger
self.audiobuffer = None
self.setObjectName("Spectrum_Widget")
self.gridLayout = QtWidgets.QGridLayout(self)
self.gridLayout.setObjectName("gridLayout")
self.PlotZoneSpect = SpectrumPlotWidget(self, sharedGLWidget,
self.logger)
self.PlotZoneSpect.setObjectName("PlotZoneSpect")
self.gridLayout.addWidget(self.PlotZoneSpect, 0, 0, 1, 1)
# initialize the class instance that will do the fft
self.proc = audioproc(self.logger)
self.maxfreq = DEFAULT_MAXFREQ
self.proc.set_maxfreq(self.maxfreq)
self.minfreq = DEFAULT_MINFREQ
self.fft_size = 2**DEFAULT_FFT_SIZE * 32
self.proc.set_fftsize(self.fft_size)
self.spec_min = DEFAULT_SPEC_MIN
self.spec_max = DEFAULT_SPEC_MAX
self.weighting = DEFAULT_WEIGHTING
self.dual_channels = False
self.response_time = DEFAULT_RESPONSE_TIME
self.update_weighting()
self.freq = self.proc.get_freq_scale()
self.old_index = 0
self.overlap = 3. / 4.
self.update_display_buffers()
# set kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
self.PlotZoneSpect.setlogfreqscale() #DEFAULT_FREQ_SCALE = 1 #log10
self.PlotZoneSpect.setfreqrange(self.minfreq, self.maxfreq)
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
self.PlotZoneSpect.setweighting(self.weighting)
self.PlotZoneSpect.set_peaks_enabled(True)
self.PlotZoneSpect.set_baseline_displayUnits(0.)
self.PlotZoneSpect.setShowFreqLabel(DEFAULT_SHOW_FREQ_LABELS)
# initialize the settings dialog
self.settings_dialog = Spectrum_Settings_Dialog(self, self.logger)
def __init__(self, parent, logger=PrintLogger()):
super().__init__(parent)
self.logger = logger
self.setObjectName(self.name)
self.gridLayout = QtWidgets.QGridLayout(self)
self.gridLayout.setObjectName("gridLayout")
self.PlotZoneSpect = SpectrumPlotWidget(self, self.logger)
self.PlotZoneSpect.setObjectName("PlotZoneSpect")
self.gridLayout.addWidget(self.PlotZoneSpect, 0, 0, 1, 1)
# initialize the class instance that will do the fft
self.proc = audioproc(self.logger)
self.maxfreq = DEFAULT_MAXFREQ
self.proc.set_maxfreq(self.maxfreq)
self.minfreq = DEFAULT_MINFREQ
self.fft_size = 2 ** DEFAULT_FFT_SIZE * 32
self.proc.set_fftsize(self.fft_size)
self.spec_min = DEFAULT_SPEC_MIN
self.spec_max = DEFAULT_SPEC_MAX
self.weighting = DEFAULT_WEIGHTING
self.dual_channels = False
self.response_time = DEFAULT_RESPONSE_TIME
self.spectrum_type = "Power" # DEFAULT_SPECTRUM_TYPE = 2
self.is_dB = True # DEFAULT_INTENSITY_SCALE = 0
self.update_weighting()
self.freq = self.proc.get_freq_scale()
self.overlap = 3. / 4.
self.data_buffer = RingBuffer(1, 4 * self.fft_size)
self.smoothing_buffer = RingBuffer(1, self.fft_size*self.overlap)
self.update_display_buffers()
# set kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
self.PlotZoneSpect.setlogfreqscale() # DEFAULT_FREQ_SCALE = 1 #log10
self.PlotZoneSpect.setfreqrange(self.minfreq, self.maxfreq)
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
self.PlotZoneSpect.setweighting(self.weighting)
self.PlotZoneSpect.set_peaks_enabled(False)
self.PlotZoneSpect.set_baseline_displayUnits(0.)
self.PlotZoneSpect.setShowFreqLabel(DEFAULT_SHOW_FREQ_LABELS)
# initialize the settings dialog
self.settings_dialog = Spectrum_Settings_Dialog(self, self.logger)
class Spectrum_Widget(QtWidgets.QWidget):
def __init__(self, parent, logger=PrintLogger()):
super().__init__(parent)
self.logger = logger
self.audiobuffer = None
self.setObjectName("Spectrum_Widget")
self.gridLayout = QtWidgets.QGridLayout(self)
self.gridLayout.setObjectName("gridLayout")
self.PlotZoneSpect = SpectrumPlotWidget(self, self.logger)
self.PlotZoneSpect.setObjectName("PlotZoneSpect")
self.gridLayout.addWidget(self.PlotZoneSpect, 0, 0, 1, 1)
# initialize the class instance that will do the fft
self.proc = audioproc(self.logger)
self.maxfreq = DEFAULT_MAXFREQ
self.proc.set_maxfreq(self.maxfreq)
self.minfreq = DEFAULT_MINFREQ
self.fft_size = 2**DEFAULT_FFT_SIZE * 32
self.proc.set_fftsize(self.fft_size)
self.spec_min = DEFAULT_SPEC_MIN
self.spec_max = DEFAULT_SPEC_MAX
self.weighting = DEFAULT_WEIGHTING
self.dual_channels = False
self.response_time = DEFAULT_RESPONSE_TIME
self.update_weighting()
self.freq = self.proc.get_freq_scale()
self.old_index = 0
self.overlap = 3. / 4.
self.update_display_buffers()
# set kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
self.PlotZoneSpect.setlogfreqscale() # DEFAULT_FREQ_SCALE = 1 #log10
self.PlotZoneSpect.setfreqrange(self.minfreq, self.maxfreq)
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
self.PlotZoneSpect.setweighting(self.weighting)
self.PlotZoneSpect.set_peaks_enabled(True)
self.PlotZoneSpect.set_baseline_displayUnits(0.)
self.PlotZoneSpect.setShowFreqLabel(DEFAULT_SHOW_FREQ_LABELS)
# initialize the settings dialog
self.settings_dialog = Spectrum_Settings_Dialog(self, self.logger)
# method
def set_buffer(self, buffer):
self.audiobuffer = buffer
self.old_index = self.audiobuffer.ringbuffer.offset
def log_spectrogram(self, sp):
# Note: implementing the log10 of the array in Cython did not bring
# any speedup.
# Idea: Instead of computing the log of the data, I could pre-compute
# a list of values associated with the colormap, and then do a search...
epsilon = 1e-30
return 10. * log10(sp + epsilon)
def handle_new_data(self, floatdata):
# we need to maintain an index of where we are in the buffer
index = self.audiobuffer.ringbuffer.offset
available = index - self.old_index
if available < 0:
# ringbuffer must have grown or something...
available = 0
self.old_index = index
# if we have enough data to add a frequency column in the time-frequency plane, compute it
needed = self.fft_size * (1. - self.overlap)
realizable = int(floor(available / needed))
if realizable > 0:
sp1n = zeros((len(self.freq), realizable), dtype=float64)
sp2n = zeros((len(self.freq), realizable), dtype=float64)
for i in range(realizable):
floatdata = self.audiobuffer.data_indexed(
self.old_index, self.fft_size)
# first channel
# FFT transform
sp1n[:, i] = self.proc.analyzelive(floatdata[0, :])
if self.dual_channels and floatdata.shape[0] > 1:
# second channel for comparison
sp2n[:, i] = self.proc.analyzelive(floatdata[1, :])
self.old_index += int(needed)
# compute the widget data
sp1 = pyx_exp_smoothed_value_numpy(self.kernel, self.alpha, sp1n,
self.dispbuffers1)
sp2 = pyx_exp_smoothed_value_numpy(self.kernel, self.alpha, sp2n,
self.dispbuffers2)
# store result for next computation
self.dispbuffers1 = sp1
self.dispbuffers2 = sp2
sp1.shape = self.freq.shape
sp2.shape = self.freq.shape
self.w.shape = self.freq.shape
if self.dual_channels and floatdata.shape[0] > 1:
dB_spectrogram = self.log_spectrogram(
sp2) - self.log_spectrogram(sp1)
else:
dB_spectrogram = self.log_spectrogram(sp1) + self.w
# the log operation and the weighting could be deffered
# to the post-weedening !
i = argmax(dB_spectrogram)
fmax = self.freq[i]
self.PlotZoneSpect.setdata(self.freq, dB_spectrogram, fmax)
# method
def canvasUpdate(self):
self.PlotZoneSpect.update()
def pause(self):
self.PlotZoneSpect.pause()
def restart(self):
self.PlotZoneSpect.restart()
def setresponsetime(self, response_time):
# time = SMOOTH_DISPLAY_TIMER_PERIOD_MS/1000. #DISPLAY
# time = 0.025 #IMPULSE setting for a sound level meter
# time = 0.125 #FAST setting for a sound level meter
# time = 1. #SLOW setting for a sound level meter
self.response_time = response_time
# an exponential smoothing filter is a simple IIR filter
# s_i = alpha*x_i + (1-alpha)*s_{i-1}
# we compute alpha so that the N most recent samples represent 100*w percent of the output
w = 0.65
delta_n = self.fft_size * (1. - self.overlap)
n = self.response_time * SAMPLING_RATE / delta_n
N = 2 * 4096
self.alpha = 1. - (1. - w)**(1. / (n + 1))
self.kernel = self.compute_kernel(self.alpha, N)
def compute_kernel(self, alpha, N):
kernel = (1. - alpha)**arange(N - 1, -1, -1)
return kernel
def update_display_buffers(self):
self.dispbuffers1 = zeros(len(self.freq))
self.dispbuffers2 = zeros(len(self.freq))
def setminfreq(self, minfreq):
self.setMinMaxFreq(minfreq, self.maxfreq)
def setmaxfreq(self, maxfreq):
self.setMinMaxFreq(self.minfreq, maxfreq)
def setMinMaxFreq(self, minfreq, maxfreq):
self.minfreq = minfreq
self.maxfreq = maxfreq
realmin = min(self.minfreq, self.maxfreq)
realmax = max(self.minfreq, self.maxfreq)
self.proc.set_maxfreq(realmax)
self.freq = self.proc.get_freq_scale()
self.update_display_buffers()
self.update_weighting()
# reset kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
self.PlotZoneSpect.setfreqrange(realmin, realmax)
def setfftsize(self, fft_size):
self.fft_size = fft_size
self.proc.set_fftsize(self.fft_size)
self.freq = self.proc.get_freq_scale()
self.update_display_buffers()
self.update_weighting()
# reset kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
def setmin(self, value):
self.spec_min = value
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
def setmax(self, value):
self.spec_max = value
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
def setweighting(self, weighting):
self.weighting = weighting
self.PlotZoneSpect.setweighting(weighting)
self.update_weighting()
def update_weighting(self):
A, B, C = self.proc.get_freq_weighting()
if self.weighting is 0:
self.w = zeros(A.shape)
elif self.weighting is 1:
self.w = A
elif self.weighting is 2:
self.w = B
else:
self.w = C
self.w.shape = (1, self.w.size)
def setdualchannels(self, dual_enabled):
self.dual_channels = dual_enabled
if dual_enabled:
self.PlotZoneSpect.set_peaks_enabled(False)
self.PlotZoneSpect.set_baseline_dataUnits(0.)
else:
self.PlotZoneSpect.set_peaks_enabled(True)
self.PlotZoneSpect.set_baseline_displayUnits(0.)
def setShowFreqLabel(self, showFreqLabel):
self.PlotZoneSpect.setShowFreqLabel(showFreqLabel)
def settings_called(self, checked):
self.settings_dialog.show()
def saveState(self, settings):
self.settings_dialog.saveState(settings)
def restoreState(self, settings):
self.settings_dialog.restoreState(settings)
class Spectrum_Widget(QtWidgets.QWidget):
def __init__(self, parent, logger=PrintLogger()):
super().__init__(parent)
self.logger = logger
self.audiobuffer = None
self.setObjectName("Spectrum_Widget")
self.gridLayout = QtWidgets.QGridLayout(self)
self.gridLayout.setObjectName("gridLayout")
self.PlotZoneSpect = SpectrumPlotWidget(self, self.logger)
self.PlotZoneSpect.setObjectName("PlotZoneSpect")
self.gridLayout.addWidget(self.PlotZoneSpect, 0, 0, 1, 1)
# initialize the class instance that will do the fft
self.proc = audioproc(self.logger)
self.maxfreq = DEFAULT_MAXFREQ
self.proc.set_maxfreq(self.maxfreq)
self.minfreq = DEFAULT_MINFREQ
self.fft_size = 2 ** DEFAULT_FFT_SIZE * 32
self.proc.set_fftsize(self.fft_size)
self.spec_min = DEFAULT_SPEC_MIN
self.spec_max = DEFAULT_SPEC_MAX
self.weighting = DEFAULT_WEIGHTING
self.dual_channels = False
self.response_time = DEFAULT_RESPONSE_TIME
self.update_weighting()
self.freq = self.proc.get_freq_scale()
self.old_index = 0
self.overlap = 3. / 4.
self.update_display_buffers()
# set kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
self.PlotZoneSpect.setlogfreqscale() # DEFAULT_FREQ_SCALE = 1 #log10
self.PlotZoneSpect.setfreqrange(self.minfreq, self.maxfreq)
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
self.PlotZoneSpect.setweighting(self.weighting)
self.PlotZoneSpect.set_peaks_enabled(True)
self.PlotZoneSpect.set_baseline_displayUnits(0.)
self.PlotZoneSpect.setShowFreqLabel(DEFAULT_SHOW_FREQ_LABELS)
# initialize the settings dialog
self.settings_dialog = Spectrum_Settings_Dialog(self, self.logger)
# method
def set_buffer(self, buffer):
self.audiobuffer = buffer
self.old_index = self.audiobuffer.ringbuffer.offset
def log_spectrogram(self, sp):
# Note: implementing the log10 of the array in Cython did not bring
# any speedup.
# Idea: Instead of computing the log of the data, I could pre-compute
# a list of values associated with the colormap, and then do a search...
epsilon = 1e-30
return 10. * log10(sp + epsilon)
def handle_new_data(self, floatdata):
# we need to maintain an index of where we are in the buffer
index = self.audiobuffer.ringbuffer.offset
available = index - self.old_index
if available < 0:
# ringbuffer must have grown or something...
available = 0
self.old_index = index
# if we have enough data to add a frequency column in the time-frequency plane, compute it
needed = self.fft_size * (1. - self.overlap)
realizable = int(floor(available / needed))
if realizable > 0:
sp1n = zeros((len(self.freq), realizable), dtype=float64)
sp2n = zeros((len(self.freq), realizable), dtype=float64)
for i in range(realizable):
floatdata = self.audiobuffer.data_indexed(self.old_index, self.fft_size)
# first channel
# FFT transform
sp1n[:, i] = self.proc.analyzelive(floatdata[0, :])
if self.dual_channels and floatdata.shape[0] > 1:
# second channel for comparison
sp2n[:, i] = self.proc.analyzelive(floatdata[1, :])
self.old_index += int(needed)
# compute the widget data
sp1 = pyx_exp_smoothed_value_numpy(self.kernel, self.alpha, sp1n, self.dispbuffers1)
sp2 = pyx_exp_smoothed_value_numpy(self.kernel, self.alpha, sp2n, self.dispbuffers2)
# store result for next computation
self.dispbuffers1 = sp1
self.dispbuffers2 = sp2
sp1.shape = self.freq.shape
sp2.shape = self.freq.shape
self.w.shape = self.freq.shape
if self.dual_channels and floatdata.shape[0] > 1:
dB_spectrogram = self.log_spectrogram(sp2) - self.log_spectrogram(sp1)
else:
dB_spectrogram = self.log_spectrogram(sp1) + self.w
# the log operation and the weighting could be deffered
# to the post-weedening !
i = argmax(dB_spectrogram)
fmax = self.freq[i]
self.PlotZoneSpect.setdata(self.freq, dB_spectrogram, fmax)
# method
def canvasUpdate(self):
if not self.isVisible():
return
def pause(self):
self.PlotZoneSpect.pause()
def restart(self):
self.PlotZoneSpect.restart()
def setresponsetime(self, response_time):
# time = SMOOTH_DISPLAY_TIMER_PERIOD_MS/1000. #DISPLAY
# time = 0.025 #IMPULSE setting for a sound level meter
# time = 0.125 #FAST setting for a sound level meter
# time = 1. #SLOW setting for a sound level meter
self.response_time = response_time
# an exponential smoothing filter is a simple IIR filter
# s_i = alpha*x_i + (1-alpha)*s_{i-1}
# we compute alpha so that the N most recent samples represent 100*w percent of the output
w = 0.65
delta_n = self.fft_size * (1. - self.overlap)
n = self.response_time * SAMPLING_RATE / delta_n
N = 2 * 4096
self.alpha = 1. - (1. - w) ** (1. / (n + 1))
self.kernel = self.compute_kernel(self.alpha, N)
def compute_kernel(self, alpha, N):
kernel = (1. - alpha) ** arange(N - 1, -1, -1)
return kernel
def update_display_buffers(self):
self.dispbuffers1 = zeros(len(self.freq))
self.dispbuffers2 = zeros(len(self.freq))
def setminfreq(self, minfreq):
self.setMinMaxFreq(minfreq, self.maxfreq)
def setmaxfreq(self, maxfreq):
self.setMinMaxFreq(self.minfreq, maxfreq)
def setMinMaxFreq(self, minfreq, maxfreq):
self.minfreq = minfreq
self.maxfreq = maxfreq
realmin = min(self.minfreq, self.maxfreq)
realmax = max(self.minfreq, self.maxfreq)
self.proc.set_maxfreq(realmax)
self.freq = self.proc.get_freq_scale()
self.update_display_buffers()
self.update_weighting()
# reset kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
self.PlotZoneSpect.setfreqrange(realmin, realmax)
def setfftsize(self, fft_size):
self.fft_size = fft_size
self.proc.set_fftsize(self.fft_size)
self.freq = self.proc.get_freq_scale()
self.update_display_buffers()
self.update_weighting()
# reset kernel and parameters for the smoothing filter
self.setresponsetime(self.response_time)
def setmin(self, value):
self.spec_min = value
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
def setmax(self, value):
self.spec_max = value
self.PlotZoneSpect.setspecrange(self.spec_min, self.spec_max)
def setweighting(self, weighting):
self.weighting = weighting
self.PlotZoneSpect.setweighting(weighting)
self.update_weighting()
def update_weighting(self):
A, B, C = self.proc.get_freq_weighting()
if self.weighting is 0:
self.w = zeros(A.shape)
elif self.weighting is 1:
self.w = A
elif self.weighting is 2:
self.w = B
else:
self.w = C
self.w.shape = (1, self.w.size)
def setdualchannels(self, dual_enabled):
self.dual_channels = dual_enabled
if dual_enabled:
self.PlotZoneSpect.set_peaks_enabled(False)
self.PlotZoneSpect.set_baseline_dataUnits(0.)
else:
self.PlotZoneSpect.set_peaks_enabled(True)
self.PlotZoneSpect.set_baseline_displayUnits(0.)
def setShowFreqLabel(self, showFreqLabel):
self.PlotZoneSpect.setShowFreqLabel(showFreqLabel)
def settings_called(self, checked):
self.settings_dialog.show()
def saveState(self, settings):
self.settings_dialog.saveState(settings)
def restoreState(self, settings):
self.settings_dialog.restoreState(settings)